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Record W2135667008 · doi:10.1109/iembs.1995.579849

Design and test of an eight-channel cochlear implant

2002· article· en· W2135667008 on OpenAlexaff
J. Mouïne, Maoxin Wei, Réjean Fontaine, F. Duval

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicFerroelectric and Piezoelectric Materials
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsResistorCapacitorElectrical engineeringCMOSMicroprocessorChipCochlear implantChannel (broadcasting)EngineeringMaterials scienceElectronic engineeringComputer scienceVoltage

Abstract

fetched live from OpenAlex

Over the past few years, an eight-channel cochlear implant has been designed and tested by our group. The stimulator electronics are built around a custom low-power 4 /spl mu/m CMOS gate array integrated circuit. The resulting chip is mounted on a suitable thick-film hybrid circuit together with a few discrete components, capacitors and resistors, used to interface the microprocessor and to provide its input data and power. The system is then housed in a hermetically sealed titanium case to ensure its long-term biocompatibility and implantation. The resulting system that is described here constitutes a very flexible and reliable device. Preliminary results are also summarized at the end.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0050.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.027
GPT teacher head0.226
Teacher spread0.199 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2002
Admission routes1
Has abstractyes

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